基于轨迹预测的车辆协同碰撞预警仿真研究

针对已有的车辆碰撞预警系统中车辆轨迹预测的误差较大问题，提出了一种基于DGPS和车载传感器的车辆轨迹预测方法,并采用扩展卡尔曼滤波，实现车辆位置的实时估计；提出了基于等加速度变化率、等横摆角加速度模型的车辆位置预测改进模型和基于V2X技术的协同碰撞预警系统（CCWS）；在此基础上，采用模糊理论，实现纵向控制仿真试验，以验证预测模型的有效性.结果表明，基于等加速度变化率、等横摆角加速度模型的车辆位置预测模型误差更小，碰撞预警系统能更早的预警或主动制动.
Aiming at the problem that the trajectory prediction error in existing vehicle collision warning system(CWS) is relatively large, a DGPS and other vehicle sensors based vehicle trajectory prediction was proposed. Real time vehicle position estimate was realized by using extended Kalman filter (EKF). Then, constant rate of acceleration change, constant yaw rate acceleration model for vehicle position prediction and V2X technology based cooperative collision warning system(CCWS) were proposed. Based on this, the longitudinal control simulation was realized by using fuzzy theory to validate the method. The simulation results show that the vehicle position prediction model based on constant rate of acceleration change, constant yaw rate acceleration model has lower error, and zCWS can get warnings or brake earlier.